Posted
by
kdawson
on Wednesday July 30, 2008 @04:43AM
from the eye-to-eye dept.

An anonymous reader writes "The folks at the Edge have published a short story by George Dyson, Engineer's Dreams. It's a piece that fiction magazines wouldn't publish because it's too technical and technical publications wouldn't print because it's too fictional. It's the story of Google's attempt to map the web turning into something else, something that should interest us. The story contains some interesting observations such as, 'This was the paradox of artificial intelligence: any system simple enough to be understandable will not be complicated enough to behave intelligently; and any system complicated enough to behave intelligently will not be simple enough to understand.' After you read it, you'll be asking the same question the author does — 'Are we searching Google, or is Google searching us?'"

Hey, we all know the unspoken rules... if you read the article, you aren't supposed to post... and if you post, you aren't supposed to read the article. That's how a million geeks can slam a site from a Slashdot link, because there surely aren't a million posts in the thread of discussion about the same article.

Sorry about crossing the 30 word barrier though, and all the pain I caused those who have read this far...

I read it; well written story that hauntingly reminds me of Arthur Clarke's "The 9 Billion Names of God"...One question: Such analog occilations in the data stream....aren't REALLY there are they? Are they?

It had a bunch of interesting excerpts, but overall I found a parallel to the "mother earth" concept.

Humans love to find patterns, it makes it easier to conceptualize and organize information. We look at our environment and find a wealth of information, when we expand our vision to include entire ecologies we find interaction between entities, and when we expand enough we become lost in the vastness of it all.

So how can we characterize all this information? We see the earth as a living organism, with a system of self-correcting processes that help sustain it's "life". A predator evolves a new advantage and the prey evolves a new defense. Overly successful species eat themselves to extinction or become eaten by a predator who is flooded with a bountiful food source.

In order to capture this ongoing balance act, we just call the pattern "life". But the exercise is left to the reader to determine the difference between the natural order and the human concept of "life as we know it"./. can refer to Riker's arguments against Data as a living life form. Pop open the back-plate of Google's head and switch it off. So long as the process requirements are in place, Google can function, but with us, once we die we are irreparably dead even when we bring the body back to life.

Oh, I'm going to take a wild stab in the dark and say, since they bothered to put the question in the headline, yes, Google is searching us. I can sometimes be bothered to RTFA, but not when it's so obviously tinfoil-hat-baiting as this.

The best argument against this kind of ridiculous assertion that somehow random information will somehow give rise to intelligence is provided in the old movie Short Circuit. The SAINT 5 robot spends all night reading the encyclopedia and when morning comes, it is suddenly an expert on everything. But its expertise is only in pure knowledge, not the rational use of that knowledge to create something beyond mere identification.

The only way for a robot to grow past its programming is to add the capability to do so. And simply having a system scan data and find correlations isn't going to be enough. There needs to be an action taken on the discovered correlations, and beyond that the actions need to be reprocessed back into the system in a feedback loop. And even further, it is necessary for the program to identify patterns and make intelligent decisions based on those patterns, but the intelligence necessary to make those decisions must come from external sources. I.e. the programmer.

It's a bit outlandish to think that just because a program is constantly watching and processing inputs that it is somehow sentient.

I swear to god, when I was in 2nd grade, I learned that it was a word that you could spell either way. And WIKI confirms it! Spellings change over time. That kid was always an insufferable smartass -- um, yeah, kid, there's only one way to spell it - NOW. Smack.

This chain of processing is done by all brains from the fruit fly to humans. Everything else is a consequential result from this process.

A human brain has very few hardwired constants and many of them they can be overridden.

Feedback loops are a natural result of action to fulfill internal needs according an internal model - that is always incomplete or wrong, see Goedel - upon the external universe. In the next step data is gathered, correlations found (which constitutes the feedback loop) and then acted out according to the adapted internal model.

A fruit fly has simple sensors, a very simple correlation engine and a tiny memory for its internal model. But that doesn't mean its following a different path than a newborn Einstein. Einstein has detailed sensors (easily surpassed by those of dogs and eagles, but still ok), a yet-unmatched correlation engine and a sufficient amount of internal model memory.

All other inputs come from the external universe and while some of them are absolutely neccessary and come from other organisms (parents, teachers), they do not impose a hard limit on Einstein: with enough correlation power, he can easily discover new facts, unknown to any of his inputs (teachers, parents).

Einsteins brain was never designed to do anything else than processing input signals, detecting correlations and contacting motor neurons to act upon its internal model. How did he discover Relativity then?

That's the hard part. If you have infinite computational resources it's really trivial to act intelligently. All you need do is enumerate all possible outcomes of all possible actions with an idealized model of the world (Godel not withstanding) and pick whichever maximizes your expected reward. You can write nice long mathematical papers on this.. or even a whole book. The question is, how do you do it with a sensible amount of processing power and memory?

All the geeks have a great laugh when Matt Groening causes Bender to become transparent and we see a 6502 inside. The joke is that Bender has about the same processing power of a C64 from the early 80s. The show is littered with additional Commodore jokes which I'm sure 90% of the viewers just don't get. But that's not what really makes it funny. What really makes it funny is that all us geeks know that you need a lot more processing power than a 6502 to do the complex things that Bender does in the complex environment he does them in. But how is that? We don't know how to do AI. We don't even have the slightest clue. For all we know, there is a tight little algorithm for AI that could run on a 6502 and produce all those crazy behaviors that Bender gets away with.

And that's the problem with AI. The allure is that some short little algorithm exists that will magically evolve into a super-human intelligence if you just could find it and hook it up to the world. After all, nature figured out, how hard could it be? This has led many a would be mad scientist to code up a genetic algorithms implementation. In fact, most every programmer I know has given it a go. The mystery of what you'll find if you give it the right fitness function is a powerful motivator - with a little magical thinking, it could be anything!

What a great post. You've accurately summarized the entire AI problem in a couple of paragraphs - however, you're missing an incredibly simple aspect. You hint at it here:

will magically evolve

Ah, yes, that's the key, isn't it? The question to ask is not "how do humans think?", it's "what prompted selection for intelligence in humans?". Combined with massive (and I really do mean massive - the human brain has a faster clock speed and more cores (ugh, bad analogy) than a supercomputer - you'd be able to effectively set up an evolving algorithm and expose it to selection pressure for intelligence.If you know what selects for intelligence, by all means post it here; I've asked every biology teacher I've had since 9th grade and never gotten a reasonable answer.

One other point to consider; organic life works in generations; mutations do not discriminate on the basis of functionality, selection does that. Code that constantly rewrites itself replacing variable names at random and swapping if's for whiles and such (while still correcting syntax - almost every DNA sequence will "compile" into some sort of protein, just most of these new proteins will be useless (or deadly). Weight the randomization algorithm towards replacing commands with other similar commands, as most mutations will be replaced with similar amino acids (IE third base pair mutations for alanine are irrelevant, while second base pair mutations will often replace alanine with a different non-polar amino acid). Note that mutation rate is approximately my chances of getting laid, so you're code still has a good chance to compile in the next version. If it doesn't, consider that mutation selected against. Fork the code about a hundred times per generation, and you're bound to get at least one that's functional. If not, go back a generation and reroll. I'm not a coder, and I have no clue how to create code that self-modifies and self-compiles, but I'm pretty sure these are the basics.

I'm not saying learning algorythms will be easy, but they may just happen in our lifetimes. The memresistor may help speed things along; we'll see in the next couple of years when memresistor RAM comes out.

I've heard that before; however it's still not a reasonable answer to the question. That's like saying intelligence selects for intelligence (which is true). The problem is more a chicken-egg issue: What triggered the first bit of intelligent selection? It has to start somewhere. Peacock's tail works because a male had a brightly colored slightly larger feather that females could use as evidence that the male possessed greater fitness. Ditto to Diopsidae, and most other sexual selections.

If you know what selects for intelligence, by all means post it here; I've asked every biology teacher I've had since 9th grade and never gotten a reasonable answer.

Maybe you should ask a more specific question.:-) If "What selects for intelligence?" means roughly the same as "Which survival problems can be solved by intelligence?" then the answer is "Pretty much all of them."

Let's take a fairly broad definition of intelligence:
1. The ability to learn which actions, in which states, lead to which outco

Of course it is a misleadingly simple abstraction when I condensed the entire work of Einstein into input, processing, output. That's the overall process and I wanted to make clear that this cycle can be repeated in a self-contained machine that may need external reference or guidance, but can easily surpass the level of sentience its ancestors had.

We do not know yet how a correlation engine and memory can artificially be made, well, we are only just now beginning to understand how the stacks of neurons in

What makes your comment really funny is, the Commodore didn't use it's CPU for everything and connect to dumb IO devices. It had a good deal more intelligence in it's various components, keeping the load on the CPU low in the same way SCSI drives don't tax the CPU like ATA does. Which is how humans work... most data doesn't ever make it to the brain, but is pre-filtered by our organs, and most complex co-ordination exhibited by our bodies is not directly orchestrated by our brain, but through various biological dumb circuits.

The Commodore 64 had more in common with how humans work than modern computers do. I expect that once we begin grappling with the "avalanche of cores" problem in a meaningful way, modern computers will begin to be programmed in a fashion more reminiscent of how biological systems work.

As you stated: correlation. He took the facts that were given, noticed something, did a few tests, and found something new.
In this manner, the human brain and a machine are very similar. Both will look at the facts, check if there's anything wrong with them, do a few tests if there is, then find something new.
The difference is, machines need to be told what to look for. Humans can act on base instinct or curiosity. As a result, machines will only check if they've been told to, and will only find what th

its expertise is only in pure knowledge, not the rational use of that knowledge to create something beyond mere identification.

Well, I guess that could make a spambot the first AI then - given that it's build to make people do things. Given the complexity of the spam/antispam race and the size of botnets it even starts to seem pseudoplausible. It would screw up the net though, and some of us might get some sun...

That could make a very interesting bit of fiction: Nigh-simultaneous emergence of the google-AI and conglomerate of spam/trojan botnet-AIs. Cue war, or long and complicated discussion (possibly the same thing for a digital lifeform), between the two on who gets to control the fate of humanity. Meanwhile, humans wonder why Google was lagging a bit for the last 10 minutes and why there's been so much comment-spam recently.

Parent is right. As long as there is no way for the programs running on Google's hardware to grow past their original programming (beyond optimization and load-balancing), there will be no Skynet.

Yes, many computer programs work in a feedback loop, and so do all organisms. But as long as only the data entry part of the loop can change, and the system lacks the flexibility to change the type of processing that takes place (the 'program'), no spontaneous evolution will occur.

Several factors are needed to get us to the bleak, dark, machine-vs-human Sci-Fi universe slashdotters know and love.

The would-be AI programs must be free to rewrite portions of themselves. Self-modifying code is generally frowned upon as being very hard to write and debug, and outside academia (evolutionary programming?), nobody is pushing it. Also, current approaches need massive amounts of processing for meager results.

The programs should be free to replicate. While Google has a lot of machines, they probably don't want runaway programs hogging the CPU cycles (they are not in the heating business). Internet-roaming malware is a much more likely than Google-sponsored code to eat over the Internets. Partly because the cheapest way to replicate is not asking for permission, and evolutionary systems will take shortcuts whenever available.

There must be evolutionary constraints to help weed the "unsucessful" strains. If a viral, self-modifying program manages to get everywhere and "kill the host" (bog down the net completely), it will no longer evolve. Fortunately, there's lots of different systems hooked up to the 'net, and colonization would be hard enough.

The first point is the most difficult. It is *not* easy to take pieces out of two programs and build a third program that does things that both do. Whatever OO promises, code is not yet "easy as lego blocks" to assemble. You need very well though-out constraints to mix code in a meaningful way - any self-modifying program would need a small, hard-to-modify kernel that would take care of the mixing mechanism. Nobody knows how to design such a kernel correctly, or what exactly to include as 'genes' (mixable code modules). Computational biology (and biology itself) are hard at work on this problem.

But mixing blocks would not be enough. A successful system would need to build new, unseen blocks by modifying existing ones -- or starting from scratch. How many different things can you say in 20 words? How many of these things make any sort of sense? And how many of those require a very, very specific context to fit into?. The way that evolution can sort this out is by, very slowly, building things that sort-of, kind-of get the job done. However you look at it, there will be huge amounts of trial-and-error involved.

And another problem is that of intelligence "scale". Imagine a super-self-modifying internet worm. The ability to probe and infect does not automatically lead to self-consciousness. There are many, many evolutionary steps from bacteria (very good at self-modification and breeding) to humans. And the current installed base of Internet-connected computers and their "stability" (the time-frame during which a given system remains 'constant') is tiny in comparison to the resources that earths' organisms have had at their disposal for evolutionary purposes. Yes, computers are way fast and this can compensate for some parallelism issues. But I still think that emerging AI is still very, very far off.

Actually, the "template-based addressing" in the story really can have some profound effects [wikipedia.org]. (My own explanation of how Tierra works here [homeunix.net].) Google becoming intelligent probably isn't one of them, but some systems are a lot more 'evolvable' [wikipedia.org] than others.

The programmer only needs to create the framework to accept inputs and process accordingly. Intelligence as we understand it is rarely wholly rational. I think this is why Neural Nets have failed to reach any state we would call intelligent, much less sentient. The framework is missing a key factor.

The only way for a robot to grow past its programming is to add the capability to do so. And simply having a system scan data and find correlations isn't going to be enough. There needs to be an action taken on the discovered correlations, and beyond that the actions need to be reprocessed back into the system in a feedback loop. And even further, it is necessary for the program to identify patterns and make intelligent decisions based on those patterns, but the intelligence necessary to make those decision

But I have to ask, is it such a bad thing?You know what it's like, you go to search for something completely innocent and porn comes up. It's not a fault or an idiosyncrasy of the interweb, it's google giving you what you really wanted.

I guess I'm not the only one who doesn't mind the porn I get offered, just the kind of porn. It's that sick, twisted, perverted and utterly gross kind of porn that comes up with the searches, the kind that I certainly do NOT want. And I'm sure I'm not the only one who thinks like this, so I doubt this could be anyone's favorite kind of porn.

I don't know who's searching who, but I do know that I no longer use Google because it's "simply the best". Relevant results are always lost in a torrent of ads, fake review links and e-stores trying to sell me something that's irrelevant.

To the point that I'm not using Google because I genuinely like it any more, but merely because I know the alternatives are even worse. In a few years' time Google went from the best to the lesser evil.

Funny choice of wording as my relevant results while searching for software or games to buy are actually really lost in pages full of.torrents - searching for '[software] -torrent' still leaves me with parking stuff, review pages and shareware sites. The best way to find the actual original homepage for a (not so popular) application is Wikipedia, up to the point where it replaced Google as my startpage because it's where I actually find what I'm looking for.They really don't need to bother with their atte

all "magical thinking" in the field of artificial intelligence was reserved for fiction.

There's so much rigorous mathematically described hooey in AI that its hard to tell the naive geniuses from the crackpot morons. Consider this paper [springerlink.com] by Solomonoff. Brilliant stuff! A fantastic read. Then, at the end, it says:

In our view, however, the most interesting situation in machine learning, arises when we do not know ahead of time what program will solve a given problem and where the machine discovers the program itself. It seems to be very hard to find out much about this by theory alone. Running experiments is crucial.

This is Solomonoff's way of reminding us that he is a mathematician and hasn't actually run any experiments. His other papers make similar pronouncements in the footnotes about the uncomputability of his math or acknowledge the requirement of perfect (aka impractical) training data, etc. He makes it abundantly clear that is work is purely theoretical and unimplementable, but does this stop enthusiastic amateurs from reading his papers and declaring that AI is "solved"? Well no, of course not.

If a system capable of being understood could not act intelligently, then why the hell do we even bother studying the human brain? And further, any attempt at creating artificial intelligence would rely on us not knowing what the hell we are doing?

I am tired of this kind of blanket assumption that anything humans can do that we don't understand or know how to reproduce artificially is somehow incapable of ever being understood or reproduced. We are not so special as to invalidate the existence of the mechanical processes that make us work.

Being understood is not a property of the system, but of the observer of the system. I am capable of observing a computer program and understanding it. Are you saying then that a computer program is capable of being understood? That is simply wrong.

At JavaOne about 3 years ago there was a boffin talk with Gosling, Joy and others and one guy raise the image of hearing something drop through his letter box and then suddenly a little bot appearing in his room with a message "don't worry I'm just indexing your house for Google"

His point was that he had two reactions to this firstly "what a huge invasion of privacy" and second "Great I'll be able to find my car keys".

Of course Google is profiling what people do as they search, indexing everything is what they are about. The question is where this impacts on privacy and what limits we want to put on it.

"Of course Google is profiling what people do as they search, indexing everything is what they are about. The question is where this impacts on privacy and what limits we want to put on it."

*don's a decent sized tin foil hat*

There are no limits we can really put on it, the NSA is already sucking up the whole damn internet, ISP's are monitorign and recording you traffic and many I'm sure sell this data illegally to advertisers. There's taps on all the packets that go through the internet in different countr

We had this discussion a little while back. The mythical AI where machines "learn" how to "think" is a long way away or possibly impossible with current technology.

The appearance of intelligence is not intelligence. A recommendations system or search engine may appear intelligent, but the part of the system that processes information "intelligently" was programmed by a person who understood the process. The computer is merely following directions.

Some knowledge based algorithms seem unpredictable when given random data. This is not intelligence either, it is more a result of unintended consequence. You can go back and figure out why it acted a certain way.

Go read about machine learning. There's plenty of things that we *can* do. It's not hard to sort the bunk from the legitimate results. Just don't look for anyone saying what we *can't* do. That's a little too pessimistic for the compsci crowd and is considered dangerous to the math crowd (who have a habit of not saying anything they can't prove).

Some knowledge based algorithms seem unpredictable when given random data. This is not intelligence either, it is more a result of unintended consequence. You can go back and figure out why it acted a certain way.

The same rules apply to people. We have a set of programming we are born with, and then we are given random data. This data and our pre-programming explains why we act a certain way. The ability to go back and figure out why we act a certain doesn't mean we aren't intelligent.

It is a mistake to assume our intelligence is something more than a program. Our programming is just less transparent to us.

The appearance of intelligence is not intelligence. A recommendations system or search engine may appear intelligent, but the part of the system that processes information "intelligently" was programmed by a person who understood the process. The computer is merely following directions.

That not true in general. It's only true for old fashioned "code forward" computing where your code is specifying what to do with the data. With connectionist approaches, genetic computing, etc (and natural evolution), it's often the data not the code that is in control, and techniques like this are usually used specifically because you don't know how to "intelligently" solve the problem, so you instead, in essence, feed the data into an architecture where it organizes itself.

Let's also note that even though in a software system a genetic algoritm is explicitly coded, that in nature it's not. You'll not find "the evolutionary algorithm" anywhere in any form in nature. Evolution is just the emergent behavior what happens when the necessary pre-conditions (parallelism, shared resources/competition, imperfect inheritence) exist. A reasonable way to view using the same approach in software is that you also are not really providing an algorithm - you are just setting up the preconditions/environment that will result in what you want happening, without you being aware or specifying how it is going to happen.

but not in the AI kind of self-discovery and discovery of the world around it way, but in the big brother kind of way.

Google is amassing huge amounts of data on us and mining it discovering patterns of our digital selves (that perhaps don't exist in the real us) and successfully making money off of it too.

This is like a private company collecting all the purchasing information you make on your credit card assigning it a score (aka credit score) and then selling the information to you and your bank, but taken to a much higher extreme.

Google is only just starting to branch into more private aspects of our lives with medical history search etc. There is no telling where all this will end, but we can make guesses.

Turing machines were being assembled into something that was not a Turing machine
The author needs a bit of theoretical computer science. However many Turing machines you assemble, you still have a Turing machine.

Google is by far the biggest threat to the national and economic security of individual countries. It is a monster, and many non-US governments will have a bad awakening when they finally realize this and it's too late.

If Google wanted to, they could already nowadways influence stock markets on a large scale or heavily influence future research in just about any discipline globally or on a per region basis just by slightly modifying their page rank algorithm. From the user data collected by Google, you can

While doing some debugging on some AJAX work, using tamper data (FF) and Fiddler (IEx) I stumbled upon some nefarious network communications between my mouse* events (over,move,out, click etc.) attached to every single link in googles search results. And there's more! Not only are these events present but they are silently inserted after the page is rendered. Some may say "well this is for older browsers", to that I say, they are not replacing the HREF property on the anchors, they are adding event handlers to mouse* events, and perhaps more that I'm not detecting. You can not see this stuff just by viewing the source. You would need to activate the event that creates the mouse* functions. E.g.: mouse over, and then mouse click gains a new event, so trying to look at the source before the mouse over event occurs yields an null function. Any attempt to look at the source code that google is running (the script handling the events) will be met with a really good obfuscator [wikipedia.org]. Google does this to just about all their public code, e.g.: google maps. The most I can realize about the extra events is that they send a LOT of information to google whenever you click on anything. But don't take my word for it, fire up FF and the latest version of Tamper Data, click 'stop on next line' or whatever engages the debugger (I can't be bothered to look, I'm working on err. something.) and mouse over or click the links on googles search results and watch your data fly over to google, in a rather secretive manner.

It may just be nothing. Every search engine tracks what link you click on, and I think this is one of the more elegant, albeit backwardly incompatible, ways of tracking what links are clicked on. Yahoo does something similar, but they use the 301 permanently moved header with a specially crafted HREF in the anchors, you can see this pretty plainly if you open up yahoo and mouse over the links, they all point to yahoo, then you're redirected to the search. From a coding perspective this is more compatible but annoying to the end user as the link is not what it says it is going to be, it's a yahoo redirector. This means if you try and copy the link from the result you'll get some yahoo bullshit. I like googles method better, but it leaves a lot to be desired in the 'forthcoming' area.

Google also maintains a network of 'adsense' tracker scripts on hundreds of thousands of 3rd party sites, I have several customers that swear by their visitor tracker. It's kinda neat, and it's free, however, I'm sure google does not just ignore the statistics gathered by its tracker. These numerous sites make up a good chunk of the internet, so even if you don't visit google, google sees you indeed. They can track every site that participates, reading referrers and IP addresses, I could imagine some very simple algorithms that could, for the most part, piece together what other non-participating sites you've visited based on the information gathered when you do eventually visit a participating site.

Google Underhandedness IMHO:
1. Adding the even handlers after the page has loaded. There may be a technical reason, but it's just creepy.
2. Sending volumes of information back after each click. There really needs to be a limit. Do you really need my browsing history!?
3. Creating a GPS like grid of sensors on 3rd party sites. This is the creepiest. Google can tell where you are, where you've been and where you're probably going to go with this, and you don't even need to visit google a single time to be added to this network! in fact you don't have any choice whatsoever in the matter!

What Google can do to fix this perception:
1. Quit obfuscating your damn code! It just makes you look guilty when you basically say "Don't look here" in something that is "sneaking" it's way into the source. It's not like google came up with the damn cure for cancer in their JS, what are you try

If you refer to the "onmousedown" event, I think you get it wrong. It just informs google that you clicked on a link.
They use javascript instead of href so they can record the rank of the result you clicked on (it's a parameter of the javascript function). This would not be possible with href.
As I'm working on a FF extension [mozilla.org] which simulates search activities to protect privacy, I investigate the javascript code (to simulate click). ASFAIK, they do not record other events than clicks. I have made couple

we should all be ashamed... if (as suggested at the end of the story) Google's internet and web page search and optimization activities resemble the dreams of a child that child is dreaming mostly of porn.

Google is obsessive about reducing HTML size for fast delivery, and that explains two of your observations.

The JS obfuscation is code reduction - all the variable names are replaced with a single letter and the white space stripped in all of google's JS code to reduce the script length (though no doubt they like the fact that this makes reverse engineering hard too.)

Adding the events after the page loads means you can loop over the array of links returned by document.getElementsByTagName("A"), instead of adding the handler as text to every link.

We're not searching Google, we're searching the Internet. Google is a tool that can be used (and often is used) to facilitate this search.

Nitpickers are the worst, particularly when they're wrong.

Google searches the internet, but we don't, whilst using it. We search Google, because all the results we want are stored at Google, within Google, and we hopefully find the result we want. Only then are we directed to a site on the internet outside of Google containing the information we searched for.

It is not entirely innaccurate to say that 'We search the internet using Google', but this assumes a logical progession: We search google > because Google searches the internet > so that we cand find what we want on the internet = We used google to search the internet.
However, contrary to your misconceptions, it is MORE not LESS accurate to say 'We search Google (to find what we want on the internet).

Nope, quite definitely searching Google. "The internet" cannot be searched, there's no protocol for it. You can search a concentration of culled pages stored in a particular place, but you're not searching the internet. You're searching what that place has stored, believing it to be a subset of the internet.

You can trivially see this with pages that present one thing to Google spiders and another to the real browsing user. Or with 404 links - they existed at the time they went in the index, but they don't exist now. It's not the internet being searched, it's the snapshot subset that's been indexed.